To catalogue similar tiles, the team used a deep learning algorithm that classified each tile based on its visual fingerprint – colours, edges, and other features unique to the tile. Then, once a tile is selected, the algorithm compares every other image to that fingerprint and returns the best matches.

The project is still in demo-mode and the developers are working on ways to increase accuracy and providing more inclusive counts. Next, they’re looking to focus on object detection at scale.